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Record W2123476449 · doi:10.1136/bmjopen-2013-002818

Quality indicators of clinical cancer care (QC<sub>3</sub>) in colorectal cancer

2013· article· en· W2123476449 on OpenAlexfundno aff
Valentina Bianchi, Alessandra Spitale, Laura Ortelli, Luca Mazzucchelli, Andrea Bordoni

Bibliographic record

VenueBMJ Open · 2013
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsnot available
FundersInstitute for Oil Sands Innovation, University of AlbertaSwiss Cancer Research FoundationCentre Hospitalier Universitaire VaudoisCooperative Research Centre for Contamination Assessment and Remediation of the EnvironmentWellcome Trust
KeywordsMedicineColorectal cancerCancerQuality (philosophy)Family medicineMedical physicsOncologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Assessing the quality of cancer care (QoCC) has become increasingly important to providers, regulators and purchasers of care worldwide. The aim of this study was to develop evidence-based quality indicators (QIs) for colorectal cancer (CRC) to be applied in a population-based setting. DESIGN: A comprehensive evidence-based literature search was performed to identify the initial list of QIs, which were then selected and developed using a two-step-modified Delphi process involving two multidisciplinary expert panels with expertise in CRC care, quality of care and epidemiology. SETTING: The QIs of the clinical cancer care (QC3) population-based project, which involves all the public and private hospitals and clinics present on the territory of Canton Ticino (South Switzerland). PARTICIPANTS: Ticino Cancer Registry, The Colorectal Cancer Working Group (CRC-WG) and the external academic Advisory Board (AB). MAIN OUTCOME MEASURES: Set of QIs which encompass the whole diagnostic-treatment process of CRC. RESULTS: Of the 149 QIs that emerged from 181 sources of literature, 104 were selected during the in-person meeting of CRC-WG. During the Delphi process, CRC-WG shortened the list to 89 QI. AB finally validated 27 QIs according to the phase of care: diagnosis (N=6), pathology (N=3), treatment (N=16) and outcome (N=2). CONCLUSIONS: Using the validated Delphi methodology, including a literature review of the evidence and integration of expert opinions from local clinicians and international experts, we were able to develop a list of QIs to assess QoCC for CRC. This will hopefully guarantee feasibility of data retrieval, as well as acceptance and translation of QIs into the daily clinical practice to improve QoCC. Moreover, evidence-based selected QIs allow one to assess immediate changes and improvements in the diagnostic-therapeutic process that could be translated into a short-term benefit for patients with a possible gain both in overall and disease-free survival.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.096
metaresearch head score (Gemma)0.182
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.507

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0960.182
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0070.013
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.124
GPT teacher head0.504
Teacher spread0.380 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2013
Admission routes1
Has abstractyes

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